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Information support for decision making. Christopher Hart 2012

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Presentation supporting a talk at the 2nd Annual Oncology Biomarkers Congress in Manchester, UK. Details several of my projects providing information to support effective clinical program design, data interpretation, and biomarker development.

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Information support for decision making. Christopher Hart 2012

  1. 1. Decisions, Decisions, Decisions Oncology Clinical Development Congress 10 October 2012 Christopher Hart Clinical Information Management Director, Oncology Clinical Discovery Team Information support for decision making
  2. 2. The Current Climate Christopher Hart | 10 October 20122 Research & Development | Biometrics & Information Science Iconograph by Reid Parham
  3. 3. Making a Meaningful Difference to Patients Supporting experts in making decisions •Focusing the efforts of our experts •Effective use of the most relevant information 3 Christopher Hart | 10 October 2012 Research & Development | Biometrics & Information Science
  4. 4. Clinical development as an iterative cycle Design Execute Interpret Decide Design decisions 4 Christopher Hart | 10 October 2012 Research & Development | Biometrics & Information Science
  5. 5. Constraints Scrutiny of R&D can increase quality 5 Christopher Hart | 10 October 2012 Research & Development | Biometrics & Information Science
  6. 6. - Create program options from study prototypes - Assess program options from an operational and a likelihood of success point of view Creative Process for Program Design 1 23 4 DELIVER PROGRAM OPTIONS FOR OPTIMAL COST, SPEED & CERTAINTY Identify questions Identify potential measures Create study prototypes Create program options - Identify what key questions need to be answered for the next Investment Decision - Identify the potential measures that could be used to answer each clinical question - Use integrative thinking to come up with different study options that could deliver each measure (i.e., consider study population, treatment, locations, etc)6 Christopher Hart | 10 October 2012 Research & Development | Biometrics & Information Science
  7. 7. Workbench - Key Benefits CREATIVITY TRANSPARENCY CUSTOMER INTIMACY STANDARDISATION Collaboration Experts assigned to address key uncertainties Knowledge re-use Leveraging knowledge from past and parallel projects Integrative thinking Superior options synthesized through multi level design process Transparent Decisions Decisions based on robust, documented evaluation of options, are tied directly to desired business outcomes Track changes and understand impact Changes are visualized and traced, with impact on related decisions marked to ensure consistency Project Teams A well defined design process, along with best practice, allows designers to focus on making expert decisions Governance Access to full thinking and rationalization behind proposals Early input of experts Ability to capture input of experts flexibly, at an early stage Recyclable process Ensure that best practice continues to be evolved, and uniformly used Recyclable knowledge Design thinking becomes accessible design knowledge Standards from the Start Standardized design will lead to standard data capture, reporting, and data utilization Christopher Hart | 10 October 2012 7Research & Development | Biometrics & Information Science
  8. 8. Building a “Workbench” for Clinical Trial Design Clinical Claims: How likely are we to succeed? Where do we need to be at next investment decision? Efficacy Claim Safety Claim Benefit Questions Risk Questions Major measure options Minor measure options Options for Design elements Assessment Comparator Design Location PopulationTreatment Benefit/Risk/Value Clinical questions are created, stated in a measurable way, aimed for next investment decision. … Study prototype options Program options Optimal CostOptimal RobustnessOptimal Speed Clinical studies Each Clinical question is broken down into potential Major and Minor measures, which are assessed. Measures are further worked up through assessing options for Design elements. Prototype studies are pulled together from Design elements. Statistical and operational information is worked up, e.g. Sample size, Duration, Power, Cost, Time Prototype studies are pulled together to form a program option optimized for Cost, Speed and Robustness. Statistical and operational information is finalized. Value Claim Value Questions 1 2 3 4 5 6 DesignremitDesignProgramoptions Christopher Hart | 10 October 2012 8Research & Development | Biometrics & Information Science
  9. 9. Measures and Design elements Identify Potential measures Each Clinical question is broken down into potential Major and Minor measures, which are assessed. Create options for Design elements A Major measure is further worked up through assessing options for Design elements. Possible Minor measures are pulled in from the same or other Clinical questions 3 4 Christopher Hart | 10 October 2012 9Research & Development | Biometrics & Information Science
  10. 10. Study prototypes and Program options Create Study prototypes Prototype studies are pulled together through combining Design element options. Statistical and operational information is worked up, e.g. Sample size, Duration, Power, Cost, Time. Create Program options Prototype studies are pulled together to form a program option optimized for Cost, Speed and Robustness. 5 6 Christopher Hart | 10 October 2012 10Research & Development | Biometrics & Information Science
  11. 11. Refining and Evaluating Options Refine At the very end of the process, the design team pulls together the appropriate options to compose Program options for Cost, Speed and Robustness. Evaluate After combining options, Workbench helps the team evaluate the options. The team defines important “Success factors”, e.g. for Location “Regions are preferred from a Patient prevalence perspective”. This captures the strategic thinking of the team and helps them use creativity to identify superior options Christopher Hart | 10 October 2012 11Research & Development | Biometrics & Information Science
  12. 12. Preliminary Design Clinical support for early projects 12 Christopher Hart | 10 October 2012 Research & Development | Biometrics & Information Science Clinical MeMo studies Human tissue target linkage Conduct Method & Model studies needed to qualify Proof of Mechanism and Proof of Principle biomarkers for use in early clinical studies Provision of human tissue for target linkage throughout the discovery / development cycle Discovery access to a clinical voice An early accessible & consolidated clinical voice into the developability of target and drug
  13. 13. Information Support Experts supporting experts 13 Christopher Hart | 10 October 2012 Research & Development | Biometrics & Information Science Chemistry and Patents Current Awareness News Company Profile and Pipeline Information Competitive Intelligence Literature and Clinical Trials Literature and Chemistry/ Patent Alerts Key Opinion Leaders and Associations Literature Linked to Full-text articles Alert System Aligned to Target Portfolio Expertise in Tools and ResourcesPatent Analysis Patent Analysis with STN Anavist Chemistry Structure and Reaction Searches IP Research Landscape Prior Art Searches - Before patent filings - New target evaluation - For alternative indications, collaborations, etc. Mapping potential opportunities Clinical Trials
  14. 14. Creating Program Options Competitive review 14 Christopher Hart | 10 October 2012 Research & Development | Biometrics & Information Science
  15. 15. Creating Program Options Competitive review 15 Christopher Hart | 10 October 2012 Research & Development | Biometrics & Information Science
  16. 16. Creating Program Options Development strategies 16 Christopher Hart | 10 October 2012 Research & Development | Biometrics & Information Science
  17. 17. Creating Program Options Development strategies 17 Christopher Hart | 10 October 2012 Research & Development | Biometrics & Information Science
  18. 18. Creating Program Options Defining reasonable duration 18 Christopher Hart | 10 October 2012 Research & Development | Biometrics & Information Science
  19. 19. Creating Program Options Defining reasonable duration 19 Christopher Hart | 10 October 2012 Research & Development | Biometrics & Information Science
  20. 20. Creating Program Options Comparative safety review 20 Christopher Hart | 10 October 2012 Research & Development | Biometrics & Information Science
  21. 21. Creating Program Options Comparative safety review 21 Christopher Hart | 10 October 2012 Research & Development | Biometrics & Information Science
  22. 22. Clinical development as an iterative cycle Design Execute Interpret Decide Decision making during the study 22 Christopher Hart | 10 October 2012 Research & Development | Biometrics & Information Science
  23. 23. Prompt Data Review • 21CFR312.32 IND safety reporting - “(b)Review of safety information . The sponsor must promptly review all information relevant to the safety of the drug … including information derived from any clinical … investigations… • ICH E6R1 - 4.11.2 Adverse events and/or laboratory abnormalities identified in the protocol as critical to safety evaluations should be reported to the sponsor according to the reporting requirements and within the time periods specified by the sponsor in the protocol. A requirement 23 Christopher Hart | 10 October 2012 Research & Development | Biometrics & Information Science
  24. 24. An Efficient Clinical Trial 24 Christopher Hart | 10 October 2012 Research & Development | Biometrics & Information Science Design Execute Interpret Safety oversight
  25. 25. A More Efficient Clinical Trial? Ongoing review 25 Christopher Hart | 10 October 2012 Research & Development | Biometrics & Information Science Design Execute Interpret Review Prepare
  26. 26. Ongoing Review Operational • Data entry lag • Set up • Cost • Resource Systemic • Standards • Technology • Training • Familiarity Obstacles 26 Christopher Hart | 10 October 2012 Research & Development | Biometrics & Information Science
  27. 27. Ongoing Review • “Statistically guided review of clinical data” • Colloquially called ‘Data Review Tool’ - S-Plus based Creating a consistent foundation 27 Christopher Hart | 10 October 2012 Research & Development | Biometrics & Information Science
  28. 28. Guided Data Review Example lab data Christopher Hart | 10 October 201228 Research & Development | Biometrics & Information Science
  29. 29. Guided Data Review Shift plots Christopher Hart | 10 October 201229 Research & Development | Biometrics & Information Science
  30. 30. Guided Data Review Adverse event incidence Christopher Hart | 10 October 201230 Research & Development | Biometrics & Information Science
  31. 31. Guided Data Review Group comparison plot Christopher Hart | 10 October 201231 Research & Development | Biometrics & Information Science
  32. 32. Guided Data Review Looking at a patient’s data Christopher Hart | 10 October 201232 Research & Development | Biometrics & Information Science
  33. 33. Ongoing Review • REACT: REal-time Analytics for Clinical Trials • We use it for the early assessment and ongoing monitoring of adverse events during a clinical trial. Putting more in the hands of the expert 33 Christopher Hart | 10 October 2012 Research & Development | Biometrics & Information Science
  34. 34. Ongoing Review Example population lab data 34 Christopher Hart | 10 October 2012 Research & Development | Biometrics & Information Science
  35. 35. Ongoing Review Example population lab data 35 Christopher Hart | 10 October 2012 Research & Development | Biometrics & Information Science
  36. 36. Ongoing Review • data review tools - real time - statistically guided - interactive - intelligible An essential activity in drug development 36 Christopher Hart | 10 October 2012 Research & Development | Biometrics & Information Science
  37. 37. Clinical development as an iterative cycle Design Execute Interpret Decide 37 Christopher Hart | 10 October 2012 Research & Development | Biometrics & Information Science
  38. 38. Set up Execute Analyze Set up Execute Analyze Accurate Forecasting Affects Analysis Sometimes things take longer than planned 38 Christopher Hart | 10 October 2012 Research & Development | Biometrics & Information Science Set up Execute Analyze D e c i d e
  39. 39. Less is More Fewer static reports help interpretation 39 Christopher Hart | 10 October 2012 Research & Development | Biometrics & Information Science
  40. 40. Traditional Trial Reporting A phase 2 study, 210 patients Christopher Hart | 10 October 201240 Research & Development | Biometrics & Information Science
  41. 41. Presenting Our Results Contemporary technology 41 Christopher Hart | 10 October 2012 Research & Development | Biometrics & Information Science
  42. 42. Setting the Rules for a Decision Design Execute Interpret Decide Design with the end in mind 42 Christopher Hart | 10 October 2012 Research & Development | Biometrics & Information Science
  43. 43. Great Design Should Give Good Results Easy, unambiguous interpretation of results 43 Christopher Hart | 10 October 2012 Research & Development | Biometrics & Information Science
  44. 44. Shades of Evidence Easy, ambiguous interpretation of results 44 Christopher Hart | 10 October 2012 Research & Development | Biometrics & Information Science
  45. 45. Complex Measures Expert interpretation is needed 45 Christopher Hart | 10 October 2012 Research & Development | Biometrics & Information Science pre post
  46. 46. Openness and Simplicity Help • Clear criteria • Explicit assumptions • Predefined analyses • Immediate access to interpretable trial data 46 Christopher Hart | 10 October 2012 Research & Development | Biometrics & Information Science
  47. 47. Setting the Rules for a Decision Design Execute Interpret Decide Anticipating changes 47 Christopher Hart | 10 October 2012 Research & Development | Biometrics & Information Science
  48. 48. To the Future Experts with information at their fingertips 48 Christopher Hart | 10 October 2012 Research & Development | Biometrics & Information Science
  49. 49. Clinical applications project Christopher Hart | 10 October 201249 Research & Development | Biometrics & Information Science
  50. 50. To the Future 50 Christopher Hart | 10 October 2012 Research & Development | Biometrics & Information Science
  51. 51. Increasing Transparency • NEJM editorial on the USA Trial and Experimental Studies Transparency Act • “…clinical trials should be conducted in the open, with full public knowledge of the question asked, the intervention tested, and the results obtained. The TEST Act is another step toward this end, and we strongly support it.” • European Medicines Agency statement - “…it will proactively publish clinical trial data and enable access to full data sets by interested parties.” • EFPIA statement - “EFPIA, the voice of the research-based pharmaceutical industry, welcomes all moves to remove perceived secrecy, as long as legitimate trade secrets are protected” The call and the response 51 Christopher Hart | 10 October 2012 Research & Development | Biometrics & Information Science
  52. 52. Linked Data Are Changing What We Can Do Linked open data in 2011 52 Christopher Hart | 10 October 2012 Research & Development | Biometrics & Information Science Linking Open Data cloud diagram, by Richard Cyganiak and Anja Jentzsch. http://lod-cloud.net/
  53. 53. Increasing Interest in Linked Data An evolving set of tools 53 Christopher Hart | 10 October 2012 Research & Development | Biometrics & Information Science
  54. 54. Open Data Let People Do More You can apply your own perspective 54 Christopher Hart | 10 October 2012 Research & Development | Biometrics & Information Science
  55. 55. Health Data Accessible? Open? • Because of PatientsLikeMe, we are better able to recognize warning signs... [and] keep things in perspective. In short, PatientsLikeMe empowers us. • PatientsLikeMe has provided me with new friends- people who are experiencing the same problems as I am. • I joined because I didn't want to feel alone anymore. Simply put. And I knew that I could be helpful [by sharing] my experience. • www.patientslikeme.com 55 Christopher Hart | 10 October 2012 Research & Development | Biometrics & Information Science [myhealthevet] provides you opportunities and tools to make informed decisions
  56. 56. 56 Christopher Hart | 10 October 2012 Research & Development | Biometrics & Information Science
  57. 57. In summary • Make better use of experts’ time by focusing effort - Make best use of available information in ways experts can use - Keep things simple - Embrace the available technologies and cultural changes to make the most meaningful difference for patients Make the biggest difference possible 57 Christopher Hart | 10 October 2012 Research & Development | Biometrics & Information Science
  58. 58. Acknowledgements • AstraZeneca - Andrew Hughes, Anita Lindsay, Louise Grochow, Laszlo Vasko, Nina Mian, Amrik Mahal,Jjames Weatherall, Harry Southworth & Dónal Landers • Thomson Reuters - Tim Miller, John Cole & Richard Chamier 58 Christopher Hart | 10 October 2012 Research & Development | Biometrics & Information Science
  59. 59. 59 Christopher Hart | 10 October 2012 Research & Development | Biometrics & Information Science Confidentiality Notice This file is private and may contain confidential and proprietary information. If you have received this file in error, please notify us and remove it from your system and note that you must not copy, distribute or take any action in reliance on it. Any unauthorized use or disclosure of the contents of this file is not permitted and may be unlawful. AstraZeneca PLC, 2 Kingdom Street, London, W2 6BD, UK, T: +44(0)20 7604 8000, F: +44 (0)20 7604 8151, www.astrazeneca.com

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